Search Results for author: Mohammad Taghi Saffar

Found 5 papers, 3 papers with code

FitVid: High-Capacity Pixel-Level Video Prediction

no code implementations29 Sep 2021 Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan

Furthermore, such an agent can internally represent the complex dynamics of the real-world and therefore can acquire a representation useful for a variety of visual perception tasks.

Image Augmentation Video Prediction +1

FitVid: Overfitting in Pixel-Level Video Prediction

1 code implementation24 Jun 2021 Mohammad Babaeizadeh, Mohammad Taghi Saffar, Suraj Nair, Sergey Levine, Chelsea Finn, Dumitru Erhan

There is a growing body of evidence that underfitting on the training data is one of the primary causes for the low quality predictions.

Image Augmentation Video Generation +1

On Trade-offs of Image Prediction in Visual Model-Based Reinforcement Learning

no code implementations1 Jan 2021 Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Dumitru Erhan, Harini Kannan, Chelsea Finn, Sergey Levine

In this paper, we study a number of design decisions for the predictive model in visual MBRL algorithms, focusing specifically on methods that use a predictive model for planning.

Model-based Reinforcement Learning reinforcement-learning +1

Models, Pixels, and Rewards: Evaluating Design Trade-offs in Visual Model-Based Reinforcement Learning

1 code implementation8 Dec 2020 Mohammad Babaeizadeh, Mohammad Taghi Saffar, Danijar Hafner, Harini Kannan, Chelsea Finn, Sergey Levine, Dumitru Erhan

In this paper, we study a number of design decisions for the predictive model in visual MBRL algorithms, focusing specifically on methods that use a predictive model for planning.

Model-based Reinforcement Learning Reinforcement Learning (RL)

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